DevSecOps Architect AI Platform Reliability

Electronic Arts creates next-level entertainment experiences that inspire players and fans around the world. Here, everyone is part of the story. Part of a community that connects across the globe. A place where creativity thrives, new perspectives are invited, and ideas matter. A team where everyone makes play happen.

Central Technology is the force multiplier, accelerating creative opportunity and progress at EA. We’re a world-class community of technologists, innovators, strategists, and orchestrators transforming interactive entertainment. Together, we power the platforms, AI-driven tools, live services, and infrastructure that ensure global scale, secure player experiences, and unlock bold new possibilities.

EA Security protects our players, employees, products, and platforms. We set security standards, support game and enterprise teams, assess risk across partners and systems, and ensure compliance with global requirements. Our work strengthens system integrity, supports fair play, and enables teams to build and operate securely at scale.

As a DevSecOps Architect, you will lead reliability, operational excellence, and infrastructure architecture across our enterprise security platforms and AI security operations ecosystem. Partnering with our Lead Systems Architect, you will build resilient platforms and serve as the operational owner for our AI SOC assistant, supporting our Security Operations, Incident Response, and Threat Intelligence teams.

Responsibilities

• Manage availability, change control, automated recovery, and incident runbooks across SIEM, forwarder fleets, and detection pipelines.

• Standardize deployments and container orchestration using Terraform, Ansible, and Docker to eliminate operational friction.

• Conduct design reviews and author architecture decision records with leadership to eliminate single points of failure.

• Build microservices, CLI utilities, and middleware connecting security platforms, data pipelines, and orchestration engines.

• Serve as primary technical point of contact and service owner for teams using our AI security assistant.

• Investigate platform anomalies and user reports across prompts, harnesses, configurations, and code.

• Resolve platform and harness issues with test-backed code fixes to prevent recurring failures.

• Author defect tickets with session IDs, execution traces, payload samples, and reproduction steps for developers.

• Track and optimize token consumption, model inference costs, and prompt caching in AWS Bedrock.

• Maintain FAQs, how-to documentation, and best-practice guides based on user questions and operational patterns.

• Design Splunk dashboards and alerting suites tracking platform health, ingestion lag, LLM latency, and adoption.

• Analyze OpenTelemetry distributed traces and JSON logs to pinpoint API latency and harness failures.

• Partner with detection engineers to validate detection logic and telemetry feeds against production benchmarks.

Qualifications
Required Qualifications:

• 10+ years of experience supporting high-availability production platforms, automated alerts, incident response, and change management.

• Experience developing API integrations, asynchronous workflows, automated tests, and modular tools in Python, Go, or TypeScript/Node.js.

• Experience analyzing logs, distributed traces, JSON payloads, and APIs using Splunk, Grafana, Datadog, Elastic, curl, or Postman.

• Experience with LLM mechanics, prompt engineering, agent orchestration, and resolving AI failure modes.

• Experience designing system architecture and resolving production code issues across enterprise platforms.

Core Skills and Experience:

• Experience with Splunk Search Processing Language (SPL), dashboard creation, and operational alerting.

• Experience with SOC alert triage workflows, incident response lifecycles, and MITRE ATT&CK techniques.

• Experience working with agentic frameworks or LLM SDKs such as LangChain, LlamaIndex, or Semantic Kernel.

• Experience with LLM evaluation datasets and observability frameworks such as Phoenix, LangSmith, or Langfuse.

• Experience configuring prompt caching, model quotas, and token monitoring in cloud AI suites like AWS Bedrock.

• Hands-on experience with OpenTelemetry (OTel) instrumentation and trace evaluation.

• Experience automating workflows across Splunk SOAR, SentinelOne, Tanium, or n8n.

• Experience in internal customer success, platform advocacy, or technical service ownership